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Obtaining subtrees from graphs: an ant colony approach

机译:从图中获取子树:蚁群方法

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The ant systems optimization approach is a new method of solving combinatorial optimization problems. It was originally introduced as a metaheuristic approach for the well-known traveling salesman problem. But it was subsequently shown to be an equally effective algorithm for solving other optimization problems. This article supplies more results for an extended ant colony algorithm, which can be used to compute a minimum cost Steiner tree from a graph. In each pass of the proposed algorithm, ants are placed at the terminal nodes of the Steiner tree to be computed. They are then allowed to move towards one another, along the edges of the graph, until they merge into a single entity. In this process, the paths taken by the ants define a Steiner tree. Edges receive reinforcement in the form of pheromone deposits along the paths taken by the ant, that is based on the quality of the Steiner tree produced. Pheromones eventually accrue most along better edges. As a result, after several iterations, a good Steiner tree can be extracted from the deposit. The algorithm can easily be used in several practical applications.
机译:蚂蚁系统优化方法是一种解决组合优化问题的新方法。它最初是作为一种著名的旅行推销员问题的元启发式方法引入的。但是后来证明它是解决其他优化问题的同等有效算法。本文为扩展的蚁群算法提供了更多结果,该算法可用于从图中计算出最小成本的Steiner树。在提出的算法的每个遍历中,将蚂蚁放置在要计算的Steiner树的终端节点上。然后允许它们沿着图的边缘彼此靠近,直到它们合并为一个实体。在此过程中,蚂蚁采用的路径定义了Steiner树。沿蚂蚁走过的路径,以信息素沉积的形式增强边缘,这取决于生成的Steiner树的质量。信息素最终会沿更好的边缘累积最多。结果,经过几次迭代,可以从矿床中提取出好的Steiner树。该算法可以轻松地在几种实际应用中使用。

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